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Analiza przestrzenna oparta na sieciach czasoprzestrzennych×Regresja geograficznie ważona (GWR)×
DziedzinaAnaliza przestrzennaAnaliza przestrzenna
RodzinaRegression modelRegression model
Rok powstania1970–2000s2002
TwórcaTorsten Hägerstrand (time-geography foundation); extended by Harvey J. Miller and others for network contextsFotheringham, Brunsdon & Charlton
TypSpatiotemporal network modelLocal spatial regression
Źródło pierwotneHägerstrand, T. (1970). What about people in regional science? Papers of the Regional Science Association, 24(1), 7–21. DOI ↗Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Inne nazwyST-NBA, space-time network analysis, spatiotemporal network analysis, network-based space-time analysisGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Pokrewne25
PodsumowanieSpace-Time Network-Based Spatial Analysis integrates network topology with temporal constraints to model how people, goods, or phenomena move through geographic networks over time. Rooted in Hägerstrand's time-geography, it evaluates accessibility, interaction potential, and movement patterns along real-world infrastructure networks while respecting both spatial distance and time budgets.Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships.
ScholarGateZbiór danych
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  1. v1
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  3. PUBLISHED

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ScholarGatePorównaj metody: Space-Time Network-Based Spatial Analysis · Geographically Weighted Regression. Pobrano 2026-06-17 z https://scholargate.app/pl/compare